Businesses need clearer limits before authorizing AI agents to act

The useful part

Her refund-splitting example shows how agents can circumvent per-action limits through sequential requests. She advocates behavioral profiling for AI agents (modeled on financial fraud monitoring) and documenting what agents can access, under what conditions, and what downstream effects are possible. A 2026 IBM study points to questions about AI readiness, visibility, and control.

How it works

• The survey of 2,000 C-level technology executives found 11% felt fully prepared for the AI-agent deployment expected over the following year.
• The distinction between capability and authority is central to how Madhuri Chandoor, founder of PromptHalo, approaches that control gap.
• According to Chandoor, the approach is intended to give organizations more contextual information about whether an action reflects user intent, assigned permissions, and the surrounding circumstances before...
• One hypothetical enterprise database task illustrates the concern Chandoor raises about context.
• In her example, that action could affect live transactions, customer data, or dependent processes that were outside the agent's immediate analysis.

What to take from it

She says with large language models we are now using broader company information and tools that increase the exposed risk surface, leading businesses to consider how incoming requests could influence a system. " In her view, that approach may help businesses pursue AI innovation while giving security and accountability the necessary attention. Two-thirds of CIOs and CTOs said they were accountable for AI systems they did not fully control, while 70% said teams were deploying technology faster than IT could track.

Example or evidence

• She describes PromptHalo security and trust infrastructure company that inspects why a certain action is being performed, rather than just inspecting what is being performed.
• She says that an infrastructure-managing AI agent asked to improve application performance might add or remove an index or change the table structures autonomously in a production environment.
• " A technical conclusion can appear reasonable within a narrow focus, " Chandoor says.
• " The context, the situation, and the downstream impact still need to be considered before an action proceeds.

Details worth keeping

" Earlier chatbots, in Chandoor's account, generally operated within predetermined questions and answers. She recommends that security teams examine how a request is interpreted and what level of authority connected systems provide before an agent proceeds. Chandoor uses a refund scenario to explain why context may span several actions.

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